Table of Contents
Simon Ratcliffe and Ludwig Schwardt have released an HTML5/Canvas backend for matplotlib. The backend is almost feature complete, and they have done a lot of work comparing their html5 rendered images with our core renderer Agg. The backend features client/server interactive navigation of matplotlib figures in an html5 compliant browser.
Fernando Perez got tired of all the boilerplate code needed to create a
figure and multiple subplots when using the matplotlib API, and wrote
subplots() helper function. Basic usage
allows you to create the figure and an array of subplots with numpy
indexing (starts with 0). e.g.:
fig, axarr = plt.subplots(2, 2) axarr[0,0].plot([1,2,3]) # upper, left
See pylab_examples example code: subplots_demo.py for several code examples.
Ian Thomas has fixed a long-standing bug that has vexed our most
talented developers for years.
now handles interior masked regions, and the boundaries of line and
filled contours coincide.
A long standing request is to support multiple calls to
show(). This has been difficult because it
is hard to get consistent behavior across operating systems, user
interface toolkits and versions. Eric Firing has done a lot of work
on rationalizing show across backends, with the desired behavior to
make show raise all newly created figures and block execution until
they are closed. Repeated calls to show should raise newly created
figures since the last call. Eric has done a lot of testing on the
user interface toolkits and versions and platforms he has access to,
but it is not possible to test them all, so please report problems to
the mailing list
and bug tracker.
You can now place an mplot3d graph into an arbitrary axes location, supporting mixing of 2D and 3D graphs in the same figure, and/or multiple 3D graphs in a single figure, using the “projection” keyword argument to add_axes or add_subplot. Thanks Ben Root.
The matplotlib trunk is probably in as good a shape as it has ever been, thanks to improved software carpentry. We now have a buildbot which runs a suite of nose regression tests on every svn commit, auto-generating a set of images and comparing them against a set of known-goods, sending emails to developers on failures with a pixel-by-pixel image comparison. Releases and release bugfixes happen in branches, allowing active new feature development to happen in the trunk while keeping the release branches stable. Thanks to Andrew Straw, Michael Droettboom and other matplotlib developers for the heavy lifting.